Measuring the Effect of Discourse Relations on Blog Summarization
This work addresses the problem of improving summarization for informal texts like blogs, showing that certain discourse relations are as useful as in traditional news, but it is incremental as it builds on existing summarization methods.
The study evaluated the impact of six discourse relations on blog summarization, finding that contingency, comparison, and illustration significantly improved summarization content in both blog and news datasets, while attribution, topic-opinion, and attributive did not.
The work presented in this paper attempts to evaluate and quantify the use of discourse relations in the context of blog summarization and compare their use to more traditional and factual texts. Specifically, we measured the usefulness of 6 discourse relations - namely comparison, contingency, illustration, attribution, topic-opinion, and attributive for the task of text summarization from blogs. We have evaluated the effect of each relation using the TAC 2008 opinion summarization dataset and compared them with the results with the DUC 2007 dataset. The results show that in both textual genres, contingency, comparison, and illustration relations provide a significant improvement on summarization content; while attribution, topic-opinion, and attributive relations do not provide a consistent and significant improvement. These results indicate that, at least for summarization, discourse relations are just as useful for informal and affective texts as for more traditional news articles.